Development of High-Performance Algorithms for the Segmentation of Fundus Images Using a Graphics Processing Unit

Diabetic retinopathy is one of the dangerous fundus diseases that leads to irreversible loss of vision. In the case of untimely or incorrect treatment, blindness occurs. Currently, laser coagulation is a common treatment method. An ophthalmologist uses a laser to apply a series of burns to the retina. The success of the operation depends entirely on the experience of the doctor. The automatic formation of a preliminary plan of coagulates allows us to solve a number of problems related to the operation, such as long manual placement of coagulates or adjustment of laser power. Thus, the probability of a doctor’s error is reduced, and the preparation time for the operation is significantly reduced. One of the key stages in the formation of the plan is the segmentation of the fundus image. This stage is carried out with the help of texture features, the calculation of which takes a long time. In relation to this, this study proposes high-performance algorithms for the segmentation of fundus images using CUDA technologies, which significantly speed up sequential versions and outperform parallel algorithms.